CAJ | 학술논문

针对低剂量CT（LDCT）图像质量退化的问题，提出了一种改进的非局部先验模型，并将基于该模型的Bayesian统计算法应用于LDCT投影降噪中。首先将方向性测度引入到传统的非局部先验模型中，构建一种改进的先验模型；同时结合基于加权欧氏距离的距离测度，提高权重系数计算的准确性；然后运用基于该先验模型的Bayesian统计算法对LDCT投影进行平滑降噪；最后依据降噪后投影，利用滤波反投影（FBP）方法进行重建，得到改善的LDCT图像。实验结果表明，与典型的传统L DC T重建算法相比，该算法在抑制噪声、去除伪影的同时，较好地保留了重建图像细节信息。
침대저제량CT（LDCT）도상질량퇴화적문제，제출료일충개진적비국부선험모형，병장기우해모형적Bayesian통계산법응용우LDCT투영강조중。수선장방향성측도인입도전통적비국부선험모형중，구건일충개진적선험모형；동시결합기우가권구씨거리적거리측도，제고권중계수계산적준학성；연후운용기우해선험모형적Bayesian통계산법대LDCT투영진행평활강조；최후의거강조후투영，이용려파반투영（FBP）방법진행중건，득도개선적LDCT도상。실험결과표명，여전형적전통L DC T중건산법상비，해산법재억제조성、거제위영적동시，교호지보류료중건도상세절신식。
Aiming at the problem that low-dose computed tomography (LDCT)image quality is de-graded,an improved nonlocal prior model is proposed and the prior-based Bayesian statistical algo-rithm is also applied to sinogram denoising for LDCT.First,the orientation measure is introduced into the traditional nonlocal prior model to construct a novel prior model.The accuracy of calculating the weight parameters is increased by incorporating the distance measure based on the weighed Eu-clidean distance into the improved prior model.Then,the Bayesian statistical algorithm is used in si-nogram smoothing for LDCT.Finally,the improved reconstructed image for LDCT is obtained by the filtered back-projection (FBP)from the smoothed projection data.Experimental results show that compared with traditional reconstruction algorithms for LDCT,the proposed algorithm is more effective in suppressing noise and eliminating streak artifacts while maintaining more reconstruction image details.